class_docstr: Abstract Scheduler.
docstr: Scheduler function given tf.Tensor step number.
  
  Args:
    step: tf.Tensor with tf.int32 or tf.int64 representing the current step
      number of training loops.
  
  Returns:
    Any tf.Tensor Scheduled value of given `step`
docstr_tok: ["Scheduler","function","given","tf.Tensor","step","number",".","Args",":","step",":","tf.Tensor","with","tf.int32","or","tf.int64","representing","the","current","step","number","of","training","loops",".","Returns",":","Any","tf.Tensor","Scheduled","value","of","given","`","step","`"]
code: def __call__(self, step: Union[int, tf.Tensor]) -> tf.Tensor:
      """Scheduler function given tf.Tensor step number.
  
      Args:
        step: tf.Tensor with tf.int32 or tf.int64 representing the current step
          number of training loops.
  
      Returns:
        Any tf.Tensor Scheduled value of given `step`
      """
      raise NotImplementedError()
  
file_path: model-optimization/tensorflow_model_optimization/python/core/common/keras/compression/schedules.py
imports: import abc
  from typing import Union, Optional
  import tensorflow
label_desc: Use image node_id 1 for calling the Scheduler obj's underlying member method code with example usage: obj.__call__(step) without return types